The fundamentals behind interventional fluoroscopy remain largely unchanged since its inception. Big advances have been made in detector sensitivity, however, clinicians still view 2D projective “shadow” images which simply integrate all information along the beam path. This often results in clinically relevant information being obscured by over or underlying anatomy.
Enhancement of blood vessels using iodinated contrast is routine, but must be used sparingly as contrast is nephrotoxic. In modern fluoroscopy suites 3D imaging is often available via semicircular C-arm rotation, i.e. cone beam CT (CBCT). However, the set-up time for CBCT (5_10 minutes) can cause a large interruption to clinical work-flow, especially if multiple acquisitions are required [11]. Set-up time includes: patient positioning to isocenter the area of interest, clearing the gantry's path of obstructions and preparing the contrast medium. In addition, the 3D nature of CBCT images requires some interaction from clinicians to scan through 2D sections to find the clinically relevant information. Repeated CBCT involves a significant radiation dose [2]. For these reasons, CBCT is not a natural interventional modality, and is unlikely to be used repeatedly during interventions to aid guidance.
Tomosynthesis was the first medical sectional modality, but was largely superseded by computed tomography after its invention in the 1970s. In the last decade, however, digital tomosynthesis (DTS) is being increasingly used for diagnosis of breast lesions and pulmonary nodules in the chest [3, 10] as it offers some of the tomographic benefits of CT but at substantially lower dose and shorter acquisition time [4]. Nevertheless, such diagnostic systems require dedicated equipment.
FIG. 1 illustrates how basic digital tomosynthesis systems operate. The top figure shows how a translation of an x-ray source with respect to a fluoroscopy screen (between positions A, B and C) produces three different fluoroscopy images (images A, B, and C) of the patient. The bottom figures then show how by shifting the images different amounts, and summing features, then different depths within the patient can be brought into focus. For example, by appropriate shifting an adding of the images A, B, and C either the sectional slice including the triangle feature or the sectional slice including the square feature may be imaged. However, it will also be seen how features in other slices either above or below the slice can cause image artefacts, as it can be seen in the respective resultant images that artefacts are causes by the other features (i.e. the square in the case of the section for the triangle, and vice versa).
Nearly all DTS systems have been proposed for diagnostic use, however, recently a 3D DTS prototype system, based on a mobile isocentric C-arm, has been proposed for intraoperative guidance of head and neck surgery [1, 2, 9]. The limited DTS arc (e.g. 20° to 90°) enabled a short acquisition time and low radiation dose causing minimal interruption to surgical work-flow [2]. However, apart from being modified for intraoperative use, the prototype still employs the same technique as diagnostic DTS systems and suffers from the same drawbacks.
In addition to the above, registration of preoperative 3D data to 2D intraoperative fluoroscopy data has been widely proposed for a number of clinical applications. Systems for radiosurgery and neurosurgery are in widespread clinical use. These systems allow overlay of preoperative data onto interventional images or allow additional information from a preoperative Computerised Tomography (CT) scan (e.g. a radiotherapy plan) to be accurately aligned to the patient.
In more detail, prior to an operation a patient is typically subjected to a CT scan of the body area where the surgery will take place. This results in a three-dimensional image of the scanned body area. However, during surgery real time 2D fluoroscopy images are obtained of the same area, using for example a C-arm type fluoroscopy machine. However, a 2D fluoroscopy image may be insufficient to allow a surgeon to determine the precise position within the body of surgical instruments or surgical implants, particularly during catheter based MIS procedures.
In order to address the drawbacks of the 2D images, it is known to augment the 2D real time image with the 3D pre-obtained image, obtained, for example from a CT scan. The problem then arises of ensuring accurate registration of the 3D image with the 2D image i.e. ensuring that the 2D image is aligned with the correct parts of the 3D image. As is known already in the art, CT position and orientation is usually defined by six rigid body parameters, being three translations X, Y, and Z, and three rotations θx, θy, and θz. These can be divided into parameters which define movements parallel to the plane of the fluoroscopy image (in plane parameters θx, Y, and Z), and parameters which define movements a component of which is normal to the fluoroscopy plane (out-of-plane parameters θy, and θz, and X). The registration problem is then one of how to manipulate these parameters such that the 3D data volume becomes aligned with the 2D image such that the surgeon can have some confidence in the registration achieved.
Various registration techniques are known in the art. Specifically, in Penney et al “An Image-Guided Surgery System to Aid Endovascular Treatment of Complex Aortic Aneurysms: Description and Initial Clinical Experience”, IPCAI 2011, LNCS 6689, pp. 13-24 the present inventors describe an intensity based registration technique which requires a starting position to be chosen by relying on visual inspection and identification of a vertebra in the fluoroscopy image.